{
 "metadata": {
  "name": "",
  "signature": "sha256:ff00b9a0fc03acd1de80a35db237d879143503145fd47a8ee76b5221147e6ac1"
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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "import pandas as pd\n",
      "from os.path import join\n",
      "\n",
      "from pylab import rcParams\n",
      "import matplotlib.pyplot as plt\n",
      "%matplotlib inline\n",
      "import seaborn as sns\n",
      "\n",
      "rcParams['figure.figsize'] = (14, 7)\n",
      "\n",
      "import nilmtk\n",
      "from nilmtk import DataSet, TimeFrame, MeterGroup, HDFDataStore\n",
      "from nilmtk.disaggregate import CombinatorialOptimisation\n",
      "from nilmtk.utils import print_dict\n",
      "from nilmtk.metrics import f1_score\n",
      "\n",
      "import warnings\n",
      "warnings.filterwarnings(\"ignore\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Demo of NILMTK v0.2 for BuildSys 2014"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Downloading data"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The full data set can be downloaded from the remote WikiEnergy database. The credentials are omitted here for security reasons."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# download_wikienergy(database_username, database_password, hdf_filename)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Loading data"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data_dir = '/home/nipun/datasets'\n",
      "we = DataSet(join(data_dir, 'wikienergy.h5'))\n",
      "print('loaded ' + str(len(we.buildings)) + ' buildings')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "loaded 239 buildings\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Examine dataset metadata"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print_dict(we.metadata)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<ul><li><strong>meter_devices</strong>: <ul><li><strong>eGauge</strong>: <ul><li><strong>max_sample_period</strong>: 120</li><li><strong>description</strong>: Measures circuit-level power demand.  Comes with 12 CTs.\n",
        "</li><li><strong>manufacturer_url</strong>: <a href=\"https://www.egauge.net\">https://www.egauge.net</a></li><li><strong>measurements</strong>: <ul><li>{'type': 'active', 'upper_limit': 5000, 'lower_limit': 0, 'physical_quantity': 'power'}</li></ul></li><li><strong>sample_period</strong>: 60</li><li><strong>wireless</strong>: False</li><li><strong>model</strong>: eGauge</li><li><strong>manufacturer</strong>: eGauge Systems LLC</li></ul></li></ul></li><li><strong>creators</strong>: <ul><li>Jim Shead</li></ul></li><li><strong>name</strong>: WikiEnergy</li><li><strong>description</strong>: Several months of power data for more than 239 different homes.</li><li><strong>number_of_buildings</strong>: 239</li><li><strong>related_documents</strong>: <ul><li><a href=\"http://wiki-energy.org/\">http://wiki-energy.org/</a></li><li><a href=\"http://wiki-energy.org/wp-content/uploads/2014/02/20140610-WikiEnergy-Exporting-Data-Instructions.pdf\">http://wiki-energy.org/wp-content/uploads/2014/02/20140610-WikiEnergy-Exporting-Data-Instructions.pdf</a></li><li><a href=\"http://wiki-energy.org/wp-content/uploads/2014/02/Database-Descriptions-20140319.pdf\">http://wiki-energy.org/wp-content/uploads/2014/02/Database-Descriptions-20140319.pdf</a></li></ul></li><li><strong>long_name</strong>: WikiEnergy database</li><li><strong>contact</strong>: jshead@pecanstreet.org</li><li><strong>geo_location</strong>: <ul><li><strong>latitude</strong>: 30.292308</li><li><strong>country</strong>: US</li><li><strong>longitude</strong>: -97.699671</li><li><strong>locality</strong>: Austin</li></ul></li><li><strong>publication_date</strong>: 2014</li><li><strong>timezone</strong>: US/Central</li><li><strong>schema</strong>: <a href=\"https://github.com/nilmtk/nilm_metadata/tree/v0.2\">https://github.com/nilmtk/nilm_metadata/tree/v0.2</a></li><li><strong>institution</strong>: Pecan Street Inc</li><li><strong>subject</strong>: Disaggregated power demand from domestic buildings.</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f829dc15ad0>"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Examine metadata for a single house"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "building_number = 22\n",
      "print_dict(we.buildings[building_number].metadata)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<ul><li><strong>instance</strong>: 22</li><li><strong>dataset</strong>: WikiEnergy</li><li><strong>original_name</strong>: 774</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f827f5b0750>"
       ]
      }
     ],
     "prompt_number": 41
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Examine sub-metered appliances"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "elec = we.buildings[building_number].elec\n",
      "elec.appliances"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 42,
       "text": [
        "[Appliance(type='fridge', instance=1),\n",
        " Appliance(type='dish washer', instance=1),\n",
        " Appliance(type='appliance', instance=1),\n",
        " Appliance(type='electric furnace', instance=1),\n",
        " Appliance(type='sockets', instance=1),\n",
        " Appliance(type='microwave', instance=1),\n",
        " Appliance(type='sockets', instance=2),\n",
        " Appliance(type='air conditioner', instance=1)]"
       ]
      }
     ],
     "prompt_number": 42
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Wiring hierarchy of meters"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "elec.draw_wiring_graph()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
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27dvLNa5du3aemRKDBg2Sr69vNSdFXbR91SodefRRjdyz56LX/ujvrw2PPaY7XnpJpmkq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\nRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f827e9bc990>"
       ]
      }
     ],
     "prompt_number": 43
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Select all fridges"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fridges = nilmtk.global_meter_group.select_using_appliances(type='fridge')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 44
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Proportion of energy per fridge"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The energy consumed by each appliance can be expressed as a proportion of the household's total energy.  Here we find the range of proportions for each fridge."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Select a subset of fridges, otherwise the computation takes a long time\n",
      "fridges_restricted = MeterGroup(fridges.meters[:5])\n",
      "\n",
      "proportion_per_fridge = fridges_restricted.proportion_of_upstream_total_per_meter()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result from metadata.\n",
        "Using cached result from metadata.\n",
        "\r",
        "1/5 ElecMeter(instance=18, building=60, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)]) = 0.049"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result from metadata.\n",
        "Using cached result from metadata.\n",
        "\r",
        "2/5 ElecMeter(instance=14, building=61, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)]) = 0.097"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result from metadata.\n",
        "Using cached result from metadata.\n",
        "\r",
        "3/5 ElecMeter(instance=8, building=63, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)]) = 0.000"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result from metadata.\n",
        "Using cached result from metadata.\n",
        "\r",
        "4/5 ElecMeter(instance=6, building=64, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)]) = 0.096"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result from metadata.\n",
        "Using cached result from metadata.\n",
        "\r",
        "5/5 ElecMeter(instance=16, building=66, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)]) = 0.083"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "proportion_per_fridge.plot(kind='bar');\n",
      "plt.title('fridge energy as proportion of total building energy');\n",
      "plt.ylabel('proportion');\n",
      "plt.xlabel('Fridge (<appliance instance>, <building instance>, <dataset name>)');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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YMMrMeyLiAOA8YAg4PjOvioj96/nHRsRjqa6hsBbVBewOArbJzCVjrdtUrZIkSZLKNjDD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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f827ee8ab50>"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# How much energy does the largest-consuming fridge consume in kWh?\n",
      "fridges.select(building=61).total_energy()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result from metadata.\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "active    79.120667\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fridges.select(building=61).plot();"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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0Ne3ko+7h1yrG3Hxdkzg5vWB2ggJfrmUsv+HaX20HADy44zBefM7JBbfGnjCS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\ntU9LQy+tip1GyESAUgW4XDWAGZ9Z1qjPye8reJ7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W/UouzaRGL+nnHW03nj9pkhqYr6vt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j6v8XE/tPPDhhTKevZ3AL4n//t7APwN+/wVc3Nz7bm5uUsAXAbgM09A//5DWrsVYH2gi4cW68Bp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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f827eec2510>"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Daily energy consumption across fridges in WikiEnergy data set"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fridges_restricted = MeterGroup(fridges.meters[:20])\n",
      "daily_energy = pd.Series([meter.average_energy_per_period(offset_alias='D') \n",
      "                           for meter in fridges_restricted.meters])\n",
      "\n",
      "daily_energy.plot(kind='hist');\n",
      "plt.title('Histogram of daily fridge energy');\n",
      "plt.xlabel('energy (kWh)');\n",
      "plt.ylabel('occurences');\n",
      "plt.legend().set_visible(False)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result from metadata.\n",
        "Using cached result from metadata.\n",
        "Using cached result from metadata."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result from metadata.\n",
        "Using cached result from metadata."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result from metadata."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result from metadata."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result from metadata."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result from metadata.\n",
        "Using cached result from metadata."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result from metadata.\n",
        "Using cached result from metadata."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result from metadata.\n",
        "Using cached result from metadata."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result from metadata.\n",
        "Using cached result from metadata."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result from metadata.\n",
        "Using cached result from metadata."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result from metadata.\n",
        "Using cached result from metadata."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "ename": "ValueError",
       "evalue": "The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
        "\u001b[1;32m<ipython-input-13-abb8c909a1b8>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      3\u001b[0m                            for meter in fridges_restricted.meters])\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m \u001b[0mdaily_energy\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkind\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'hist'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m;\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      6\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtitle\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Histogram of daily fridge energy'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m;\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      7\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mxlabel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'energy (kWh)'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m;\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/pandas/tools/plotting.pyc\u001b[0m in \u001b[0;36mplot_series\u001b[1;34m(data, kind, ax, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, label, secondary_y, **kwds)\u001b[0m\n\u001b[0;32m   2485\u001b[0m                  \u001b[0myerr\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0myerr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mxerr\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mxerr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2486\u001b[0m                  \u001b[0mlabel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlabel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msecondary_y\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msecondary_y\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2487\u001b[1;33m                  **kwds)\n\u001b[0m\u001b[0;32m   2488\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2489\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/pandas/tools/plotting.pyc\u001b[0m in \u001b[0;36m_plot\u001b[1;34m(data, x, y, subplots, ax, kind, **kwds)\u001b[0m\n\u001b[0;32m   2291\u001b[0m         \u001b[0mplot_obj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mklass\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msubplots\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msubplots\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mkind\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2292\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2293\u001b[1;33m     \u001b[0mplot_obj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgenerate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2294\u001b[0m     \u001b[0mplot_obj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2295\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mplot_obj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/pandas/tools/plotting.pyc\u001b[0m in \u001b[0;36mgenerate\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    915\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    916\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mgenerate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 917\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_args_adjust\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    918\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_compute_plot_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    919\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_setup_subplots\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/pandas/tools/plotting.pyc\u001b[0m in \u001b[0;36m_args_adjust\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1914\u001b[0m             hist, self.bins = np.histogram(values, bins=self.bins,\n\u001b[0;32m   1915\u001b[0m                                         \u001b[0mrange\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkwds\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'range'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1916\u001b[1;33m                                         weights=self.kwds.get('weights', None))\n\u001b[0m\u001b[0;32m   1917\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1918\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mcom\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mis_list_like\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbottom\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/numpy/lib/function_base.pyc\u001b[0m in \u001b[0;36mhistogram\u001b[1;34m(a, bins, range, normed, weights, density)\u001b[0m\n\u001b[0;32m    185\u001b[0m                 \u001b[0mrange\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    186\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 187\u001b[1;33m                 \u001b[0mrange\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    188\u001b[0m         \u001b[0mmn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mmi\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m0.0\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mmi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    189\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mmn\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0mmx\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/numpy/core/_methods.pyc\u001b[0m in \u001b[0;36m_amin\u001b[1;34m(a, axis, out, keepdims)\u001b[0m\n\u001b[0;32m     27\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     28\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_amin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mout\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkeepdims\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 29\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mumr_minimum\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mout\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkeepdims\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     30\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     31\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_sum\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mout\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkeepdims\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/pandas/core/generic.pyc\u001b[0m in \u001b[0;36m__nonzero__\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    690\u001b[0m         raise ValueError(\"The truth value of a {0} is ambiguous. \"\n\u001b[0;32m    691\u001b[0m                          \u001b[1;34m\"Use a.empty, a.bool(), a.item(), a.any() or a.all().\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 692\u001b[1;33m                          .format(self.__class__.__name__))\n\u001b[0m\u001b[0;32m    693\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    694\u001b[0m     \u001b[0m__bool__\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m__nonzero__\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;31mValueError\u001b[0m: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()."
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Plot sub-metered data for a single day"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df  = elec.power_series_all_data()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 85
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print([meter.appliance_label() for meter in elec.meters[1:]])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[\"('air conditioner', 1)\", \"('dish washer', 1)\", \"('electric furnace', 1)\", \"('sockets', 1)\", \"('sockets', 2)\", \"('microwave', 1)\", \"('fridge', 1)\", \"('appliance', 1)\"]\n"
       ]
      }
     ],
     "prompt_number": 86
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.DataFrame({meter.appliance_label():meter.power_series_all_data() for meter in elec.meters[1:]}, index=elec.meters[1].power_series_all_data().index)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 87
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>('air conditioner', 1)</th>\n",
        "      <th>('appliance', 1)</th>\n",
        "      <th>('dish washer', 1)</th>\n",
        "      <th>('electric furnace', 1)</th>\n",
        "      <th>('fridge', 1)</th>\n",
        "      <th>('microwave', 1)</th>\n",
        "      <th>('sockets', 1)</th>\n",
        "      <th>('sockets', 2)</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>localminute</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:00:00-05:00</th>\n",
        "      <td> 3805</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 859</td>\n",
        "      <td>  86</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:01:00-05:00</th>\n",
        "      <td> 3809</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 858</td>\n",
        "      <td>  93</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:02:00-05:00</th>\n",
        "      <td> 3794</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 857</td>\n",
        "      <td>  87</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:03:00-05:00</th>\n",
        "      <td> 3828</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 858</td>\n",
        "      <td>  88</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:04:00-05:00</th>\n",
        "      <td> 3824</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 858</td>\n",
        "      <td>  88</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:05:00-05:00</th>\n",
        "      <td> 1620</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 858</td>\n",
        "      <td>  89</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:06:00-05:00</th>\n",
        "      <td>    0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 841</td>\n",
        "      <td>  89</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:07:00-05:00</th>\n",
        "      <td>    0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 628</td>\n",
        "      <td>  89</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:08:00-05:00</th>\n",
        "      <td>    0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 627</td>\n",
        "      <td>  89</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:09:00-05:00</th>\n",
        "      <td>    0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 626</td>\n",
        "      <td>  90</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:10:00-05:00</th>\n",
        "      <td>    0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 626</td>\n",
        "      <td>  90</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:11:00-05:00</th>\n",
        "      <td>    0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 625</td>\n",
        "      <td>  91</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:12:00-05:00</th>\n",
        "      <td> 2778</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 782</td>\n",
        "      <td>  91</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:13:00-05:00</th>\n",
        "      <td> 3834</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 851</td>\n",
        "      <td>  91</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:14:00-05:00</th>\n",
        "      <td> 3859</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 850</td>\n",
        "      <td>  91</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:15:00-05:00</th>\n",
        "      <td> 3868</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 849</td>\n",
        "      <td>  91</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:16:00-05:00</th>\n",
        "      <td> 3853</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 845</td>\n",
        "      <td>  92</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:17:00-05:00</th>\n",
        "      <td> 3807</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 846</td>\n",
        "      <td>  92</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:18:00-05:00</th>\n",
        "      <td> 3833</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 845</td>\n",
        "      <td>  92</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:19:00-05:00</th>\n",
        "      <td> 3799</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 846</td>\n",
        "      <td>  92</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:20:00-05:00</th>\n",
        "      <td> 3830</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 846</td>\n",
        "      <td>  92</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:21:00-05:00</th>\n",
        "      <td> 3840</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 850</td>\n",
        "      <td>  92</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:22:00-05:00</th>\n",
        "      <td> 3837</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 854</td>\n",
        "      <td>  92</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:23:00-05:00</th>\n",
        "      <td> 3813</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 854</td>\n",
        "      <td>  91</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:24:00-05:00</th>\n",
        "      <td> 3799</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 854</td>\n",
        "      <td>  91</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:25:00-05:00</th>\n",
        "      <td> 1749</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 855</td>\n",
        "      <td>  91</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:26:00-05:00</th>\n",
        "      <td>    0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 845</td>\n",
        "      <td>  91</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:27:00-05:00</th>\n",
        "      <td>    0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 627</td>\n",
        "      <td>  93</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:28:00-05:00</th>\n",
        "      <td>    0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 625</td>\n",
        "      <td>  94</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 12:29:00-05:00</th>\n",
        "      <td>    0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 623</td>\n",
        "      <td> 123</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:00:00-05:00</th>\n",
        "      <td> 3997</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 843</td>\n",
        "      <td> 100</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:01:00-05:00</th>\n",
        "      <td> 3966</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 843</td>\n",
        "      <td> 100</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:02:00-05:00</th>\n",
        "      <td> 3962</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 840</td>\n",
        "      <td> 100</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:03:00-05:00</th>\n",
        "      <td> 3997</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 839</td>\n",
        "      <td> 100</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:04:00-05:00</th>\n",
        "      <td> 3970</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 837</td>\n",
        "      <td>  96</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:05:00-05:00</th>\n",
        "      <td> 3956</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 836</td>\n",
        "      <td>  95</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:06:00-05:00</th>\n",
        "      <td> 3997</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 834</td>\n",
        "      <td>  94</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:07:00-05:00</th>\n",
        "      <td> 3985</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 834</td>\n",
        "      <td>  94</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:08:00-05:00</th>\n",
        "      <td> 4003</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 834</td>\n",
        "      <td>  94</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:09:00-05:00</th>\n",
        "      <td> 4010</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 833</td>\n",
        "      <td>  94</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:10:00-05:00</th>\n",
        "      <td> 3986</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 835</td>\n",
        "      <td>  94</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:11:00-05:00</th>\n",
        "      <td> 3958</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 837</td>\n",
        "      <td>  94</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:12:00-05:00</th>\n",
        "      <td> 3968</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 837</td>\n",
        "      <td>  94</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:13:00-05:00</th>\n",
        "      <td> 3950</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 838</td>\n",
        "      <td>  94</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:14:00-05:00</th>\n",
        "      <td> 3983</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 839</td>\n",
        "      <td>  94</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:15:00-05:00</th>\n",
        "      <td> 4010</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 841</td>\n",
        "      <td>  94</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:16:00-05:00</th>\n",
        "      <td> 3963</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 841</td>\n",
        "      <td>  94</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:17:00-05:00</th>\n",
        "      <td> 4007</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 841</td>\n",
        "      <td>  94</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:18:00-05:00</th>\n",
        "      <td> 3991</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 842</td>\n",
        "      <td>  94</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:19:00-05:00</th>\n",
        "      <td> 3971</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 842</td>\n",
        "      <td>  93</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:20:00-05:00</th>\n",
        "      <td> 3958</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 843</td>\n",
        "      <td>  93</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:21:00-05:00</th>\n",
        "      <td> 3969</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 844</td>\n",
        "      <td>  93</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:22:00-05:00</th>\n",
        "      <td> 3969</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 843</td>\n",
        "      <td>  93</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:23:00-05:00</th>\n",
        "      <td> 3951</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 840</td>\n",
        "      <td>  93</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:24:00-05:00</th>\n",
        "      <td> 3983</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 839</td>\n",
        "      <td>  93</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:25:00-05:00</th>\n",
        "      <td> 3974</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 839</td>\n",
        "      <td>  93</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:26:00-05:00</th>\n",
        "      <td> 3968</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 837</td>\n",
        "      <td>  93</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:27:00-05:00</th>\n",
        "      <td> 3981</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 835</td>\n",
        "      <td>  93</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:28:00-05:00</th>\n",
        "      <td> 3978</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 834</td>\n",
        "      <td>  93</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-05-04 15:29:00-05:00</th>\n",
        "      <td> 3992</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 834</td>\n",
        "      <td>  93</td>\n",
        "      <td> 14</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>210 rows \u00d7 8 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 88,
       "text": [
        "                           ('air conditioner', 1)  ('appliance', 1)  \\\n",
        "localminute                                                           \n",
        "2014-05-04 12:00:00-05:00                    3805                 0   \n",
        "2014-05-04 12:01:00-05:00                    3809                 0   \n",
        "2014-05-04 12:02:00-05:00                    3794                 0   \n",
        "2014-05-04 12:03:00-05:00                    3828                 0   \n",
        "2014-05-04 12:04:00-05:00                    3824                 0   \n",
        "2014-05-04 12:05:00-05:00                    1620                 0   \n",
        "2014-05-04 12:06:00-05:00                       0                 0   \n",
        "2014-05-04 12:07:00-05:00                       0                 0   \n",
        "2014-05-04 12:08:00-05:00                       0                 0   \n",
        "2014-05-04 12:09:00-05:00                       0                 0   \n",
        "2014-05-04 12:10:00-05:00                       0                 0   \n",
        "2014-05-04 12:11:00-05:00                       0                 0   \n",
        "2014-05-04 12:12:00-05:00                    2778                 0   \n",
        "2014-05-04 12:13:00-05:00                    3834                 0   \n",
        "2014-05-04 12:14:00-05:00                    3859                 0   \n",
        "2014-05-04 12:15:00-05:00                    3868                 0   \n",
        "2014-05-04 12:16:00-05:00                    3853                 0   \n",
        "2014-05-04 12:17:00-05:00                    3807                 0   \n",
        "2014-05-04 12:18:00-05:00                    3833                 0   \n",
        "2014-05-04 12:19:00-05:00                    3799                 0   \n",
        "2014-05-04 12:20:00-05:00                    3830                 0   \n",
        "2014-05-04 12:21:00-05:00                    3840                 0   \n",
        "2014-05-04 12:22:00-05:00                    3837                 0   \n",
        "2014-05-04 12:23:00-05:00                    3813                 0   \n",
        "2014-05-04 12:24:00-05:00                    3799                 0   \n",
        "2014-05-04 12:25:00-05:00                    1749                 0   \n",
        "2014-05-04 12:26:00-05:00                       0                 0   \n",
        "2014-05-04 12:27:00-05:00                       0                 0   \n",
        "2014-05-04 12:28:00-05:00                       0                 0   \n",
        "2014-05-04 12:29:00-05:00                       0                 0   \n",
        "...                                           ...               ...   \n",
        "2014-05-04 15:00:00-05:00                    3997                 0   \n",
        "2014-05-04 15:01:00-05:00                    3966                 0   \n",
        "2014-05-04 15:02:00-05:00                    3962                 0   \n",
        "2014-05-04 15:03:00-05:00                    3997                 0   \n",
        "2014-05-04 15:04:00-05:00                    3970                 0   \n",
        "2014-05-04 15:05:00-05:00                    3956                 0   \n",
        "2014-05-04 15:06:00-05:00                    3997                 0   \n",
        "2014-05-04 15:07:00-05:00                    3985                 0   \n",
        "2014-05-04 15:08:00-05:00                    4003                 0   \n",
        "2014-05-04 15:09:00-05:00                    4010                 0   \n",
        "2014-05-04 15:10:00-05:00                    3986                 0   \n",
        "2014-05-04 15:11:00-05:00                    3958                 0   \n",
        "2014-05-04 15:12:00-05:00                    3968                 0   \n",
        "2014-05-04 15:13:00-05:00                    3950                 0   \n",
        "2014-05-04 15:14:00-05:00                    3983                 0   \n",
        "2014-05-04 15:15:00-05:00                    4010                 0   \n",
        "2014-05-04 15:16:00-05:00                    3963                 0   \n",
        "2014-05-04 15:17:00-05:00                    4007                 0   \n",
        "2014-05-04 15:18:00-05:00                    3991                 0   \n",
        "2014-05-04 15:19:00-05:00                    3971                 0   \n",
        "2014-05-04 15:20:00-05:00                    3958                 0   \n",
        "2014-05-04 15:21:00-05:00                    3969                 0   \n",
        "2014-05-04 15:22:00-05:00                    3969                 0   \n",
        "2014-05-04 15:23:00-05:00                    3951                 0   \n",
        "2014-05-04 15:24:00-05:00                    3983                 0   \n",
        "2014-05-04 15:25:00-05:00                    3974                 0   \n",
        "2014-05-04 15:26:00-05:00                    3968                 0   \n",
        "2014-05-04 15:27:00-05:00                    3981                 0   \n",
        "2014-05-04 15:28:00-05:00                    3978                 0   \n",
        "2014-05-04 15:29:00-05:00                    3992                 0   \n",
        "\n",
        "                           ('dish washer', 1)  ('electric furnace', 1)  \\\n",
        "localminute                                                              \n",
        "2014-05-04 12:00:00-05:00                   0                      859   \n",
        "2014-05-04 12:01:00-05:00                   0                      858   \n",
        "2014-05-04 12:02:00-05:00                   0                      857   \n",
        "2014-05-04 12:03:00-05:00                   0                      858   \n",
        "2014-05-04 12:04:00-05:00                   0                      858   \n",
        "2014-05-04 12:05:00-05:00                   0                      858   \n",
        "2014-05-04 12:06:00-05:00                   0                      841   \n",
        "2014-05-04 12:07:00-05:00                   0                      628   \n",
        "2014-05-04 12:08:00-05:00                   0                      627   \n",
        "2014-05-04 12:09:00-05:00                   0                      626   \n",
        "2014-05-04 12:10:00-05:00                   0                      626   \n",
        "2014-05-04 12:11:00-05:00                   0                      625   \n",
        "2014-05-04 12:12:00-05:00                   0                      782   \n",
        "2014-05-04 12:13:00-05:00                   0                      851   \n",
        "2014-05-04 12:14:00-05:00                   0                      850   \n",
        "2014-05-04 12:15:00-05:00                   0                      849   \n",
        "2014-05-04 12:16:00-05:00                   0                      845   \n",
        "2014-05-04 12:17:00-05:00                   0                      846   \n",
        "2014-05-04 12:18:00-05:00                   0                      845   \n",
        "2014-05-04 12:19:00-05:00                   0                      846   \n",
        "2014-05-04 12:20:00-05:00                   0                      846   \n",
        "2014-05-04 12:21:00-05:00                   0                      850   \n",
        "2014-05-04 12:22:00-05:00                   0                      854   \n",
        "2014-05-04 12:23:00-05:00                   0                      854   \n",
        "2014-05-04 12:24:00-05:00                   0                      854   \n",
        "2014-05-04 12:25:00-05:00                   0                      855   \n",
        "2014-05-04 12:26:00-05:00                   0                      845   \n",
        "2014-05-04 12:27:00-05:00                   0                      627   \n",
        "2014-05-04 12:28:00-05:00                   0                      625   \n",
        "2014-05-04 12:29:00-05:00                   0                      623   \n",
        "...                                       ...                      ...   \n",
        "2014-05-04 15:00:00-05:00                   0                      843   \n",
        "2014-05-04 15:01:00-05:00                   0                      843   \n",
        "2014-05-04 15:02:00-05:00                   0                      840   \n",
        "2014-05-04 15:03:00-05:00                   0                      839   \n",
        "2014-05-04 15:04:00-05:00                   0                      837   \n",
        "2014-05-04 15:05:00-05:00                   0                      836   \n",
        "2014-05-04 15:06:00-05:00                   0                      834   \n",
        "2014-05-04 15:07:00-05:00                   0                      834   \n",
        "2014-05-04 15:08:00-05:00                   0                      834   \n",
        "2014-05-04 15:09:00-05:00                   0                      833   \n",
        "2014-05-04 15:10:00-05:00                   0                      835   \n",
        "2014-05-04 15:11:00-05:00                   0                      837   \n",
        "2014-05-04 15:12:00-05:00                   0                      837   \n",
        "2014-05-04 15:13:00-05:00                   0                      838   \n",
        "2014-05-04 15:14:00-05:00                   0                      839   \n",
        "2014-05-04 15:15:00-05:00                   0                      841   \n",
        "2014-05-04 15:16:00-05:00                   0                      841   \n",
        "2014-05-04 15:17:00-05:00                   0                      841   \n",
        "2014-05-04 15:18:00-05:00                   0                      842   \n",
        "2014-05-04 15:19:00-05:00                   0                      842   \n",
        "2014-05-04 15:20:00-05:00                   0                      843   \n",
        "2014-05-04 15:21:00-05:00                   0                      844   \n",
        "2014-05-04 15:22:00-05:00                   0                      843   \n",
        "2014-05-04 15:23:00-05:00                   0                      840   \n",
        "2014-05-04 15:24:00-05:00                   0                      839   \n",
        "2014-05-04 15:25:00-05:00                   0                      839   \n",
        "2014-05-04 15:26:00-05:00                   0                      837   \n",
        "2014-05-04 15:27:00-05:00                   0                      835   \n",
        "2014-05-04 15:28:00-05:00                   0                      834   \n",
        "2014-05-04 15:29:00-05:00                   0                      834   \n",
        "\n",
        "                           ('fridge', 1)  ('microwave', 1)  ('sockets', 1)  \\\n",
        "localminute                                                                  \n",
        "2014-05-04 12:00:00-05:00             86                14               0   \n",
        "2014-05-04 12:01:00-05:00             93                14               0   \n",
        "2014-05-04 12:02:00-05:00             87                14               0   \n",
        "2014-05-04 12:03:00-05:00             88                14               0   \n",
        "2014-05-04 12:04:00-05:00             88                14               0   \n",
        "2014-05-04 12:05:00-05:00             89                14               0   \n",
        "2014-05-04 12:06:00-05:00             89                14               0   \n",
        "2014-05-04 12:07:00-05:00             89                14               0   \n",
        "2014-05-04 12:08:00-05:00             89                14               0   \n",
        "2014-05-04 12:09:00-05:00             90                14               0   \n",
        "2014-05-04 12:10:00-05:00             90                14               0   \n",
        "2014-05-04 12:11:00-05:00             91                14               0   \n",
        "2014-05-04 12:12:00-05:00             91                14               0   \n",
        "2014-05-04 12:13:00-05:00             91                14               0   \n",
        "2014-05-04 12:14:00-05:00             91                14               0   \n",
        "2014-05-04 12:15:00-05:00             91                14               0   \n",
        "2014-05-04 12:16:00-05:00             92                14               0   \n",
        "2014-05-04 12:17:00-05:00             92                14               0   \n",
        "2014-05-04 12:18:00-05:00             92                14               0   \n",
        "2014-05-04 12:19:00-05:00             92                14               0   \n",
        "2014-05-04 12:20:00-05:00             92                14               0   \n",
        "2014-05-04 12:21:00-05:00             92                14               0   \n",
        "2014-05-04 12:22:00-05:00             92                14               0   \n",
        "2014-05-04 12:23:00-05:00             91                14               0   \n",
        "2014-05-04 12:24:00-05:00             91                14               0   \n",
        "2014-05-04 12:25:00-05:00             91                14               0   \n",
        "2014-05-04 12:26:00-05:00             91                14               0   \n",
        "2014-05-04 12:27:00-05:00             93                14               0   \n",
        "2014-05-04 12:28:00-05:00             94                14               0   \n",
        "2014-05-04 12:29:00-05:00            123                14               0   \n",
        "...                                  ...               ...             ...   \n",
        "2014-05-04 15:00:00-05:00            100                14               0   \n",
        "2014-05-04 15:01:00-05:00            100                14               0   \n",
        "2014-05-04 15:02:00-05:00            100                14               0   \n",
        "2014-05-04 15:03:00-05:00            100                14               0   \n",
        "2014-05-04 15:04:00-05:00             96                14               0   \n",
        "2014-05-04 15:05:00-05:00             95                14               0   \n",
        "2014-05-04 15:06:00-05:00             94                14               0   \n",
        "2014-05-04 15:07:00-05:00             94                14               0   \n",
        "2014-05-04 15:08:00-05:00             94                14               0   \n",
        "2014-05-04 15:09:00-05:00             94                14               0   \n",
        "2014-05-04 15:10:00-05:00             94                14               0   \n",
        "2014-05-04 15:11:00-05:00             94                14               0   \n",
        "2014-05-04 15:12:00-05:00             94                14               0   \n",
        "2014-05-04 15:13:00-05:00             94                14               0   \n",
        "2014-05-04 15:14:00-05:00             94                14               0   \n",
        "2014-05-04 15:15:00-05:00             94                14               0   \n",
        "2014-05-04 15:16:00-05:00             94                14               0   \n",
        "2014-05-04 15:17:00-05:00             94                14               0   \n",
        "2014-05-04 15:18:00-05:00             94                14               0   \n",
        "2014-05-04 15:19:00-05:00             93                14               0   \n",
        "2014-05-04 15:20:00-05:00             93                14               0   \n",
        "2014-05-04 15:21:00-05:00             93                14               0   \n",
        "2014-05-04 15:22:00-05:00             93                14               0   \n",
        "2014-05-04 15:23:00-05:00             93                14               0   \n",
        "2014-05-04 15:24:00-05:00             93                14               0   \n",
        "2014-05-04 15:25:00-05:00             93                14               0   \n",
        "2014-05-04 15:26:00-05:00             93                14               0   \n",
        "2014-05-04 15:27:00-05:00             93                14               0   \n",
        "2014-05-04 15:28:00-05:00             93                14               0   \n",
        "2014-05-04 15:29:00-05:00             93                14               0   \n",
        "\n",
        "                           ('sockets', 2)  \n",
        "localminute                                \n",
        "2014-05-04 12:00:00-05:00               0  \n",
        "2014-05-04 12:01:00-05:00               0  \n",
        "2014-05-04 12:02:00-05:00               0  \n",
        "2014-05-04 12:03:00-05:00               0  \n",
        "2014-05-04 12:04:00-05:00               0  \n",
        "2014-05-04 12:05:00-05:00               0  \n",
        "2014-05-04 12:06:00-05:00               0  \n",
        "2014-05-04 12:07:00-05:00               0  \n",
        "2014-05-04 12:08:00-05:00               0  \n",
        "2014-05-04 12:09:00-05:00               0  \n",
        "2014-05-04 12:10:00-05:00               0  \n",
        "2014-05-04 12:11:00-05:00               0  \n",
        "2014-05-04 12:12:00-05:00               0  \n",
        "2014-05-04 12:13:00-05:00               0  \n",
        "2014-05-04 12:14:00-05:00               0  \n",
        "2014-05-04 12:15:00-05:00               0  \n",
        "2014-05-04 12:16:00-05:00               0  \n",
        "2014-05-04 12:17:00-05:00               0  \n",
        "2014-05-04 12:18:00-05:00               0  \n",
        "2014-05-04 12:19:00-05:00               0  \n",
        "2014-05-04 12:20:00-05:00               0  \n",
        "2014-05-04 12:21:00-05:00               0  \n",
        "2014-05-04 12:22:00-05:00               0  \n",
        "2014-05-04 12:23:00-05:00               0  \n",
        "2014-05-04 12:24:00-05:00               0  \n",
        "2014-05-04 12:25:00-05:00               0  \n",
        "2014-05-04 12:26:00-05:00               0  \n",
        "2014-05-04 12:27:00-05:00               0  \n",
        "2014-05-04 12:28:00-05:00               0  \n",
        "2014-05-04 12:29:00-05:00               0  \n",
        "...                                   ...  \n",
        "2014-05-04 15:00:00-05:00               0  \n",
        "2014-05-04 15:01:00-05:00               0  \n",
        "2014-05-04 15:02:00-05:00               0  \n",
        "2014-05-04 15:03:00-05:00               0  \n",
        "2014-05-04 15:04:00-05:00               0  \n",
        "2014-05-04 15:05:00-05:00               0  \n",
        "2014-05-04 15:06:00-05:00               0  \n",
        "2014-05-04 15:07:00-05:00               0  \n",
        "2014-05-04 15:08:00-05:00               0  \n",
        "2014-05-04 15:09:00-05:00               0  \n",
        "2014-05-04 15:10:00-05:00               0  \n",
        "2014-05-04 15:11:00-05:00               0  \n",
        "2014-05-04 15:12:00-05:00               0  \n",
        "2014-05-04 15:13:00-05:00               0  \n",
        "2014-05-04 15:14:00-05:00               0  \n",
        "2014-05-04 15:15:00-05:00               0  \n",
        "2014-05-04 15:16:00-05:00               0  \n",
        "2014-05-04 15:17:00-05:00               0  \n",
        "2014-05-04 15:18:00-05:00               0  \n",
        "2014-05-04 15:19:00-05:00               0  \n",
        "2014-05-04 15:20:00-05:00               0  \n",
        "2014-05-04 15:21:00-05:00               0  \n",
        "2014-05-04 15:22:00-05:00               0  \n",
        "2014-05-04 15:23:00-05:00               0  \n",
        "2014-05-04 15:24:00-05:00               0  \n",
        "2014-05-04 15:25:00-05:00               0  \n",
        "2014-05-04 15:26:00-05:00               0  \n",
        "2014-05-04 15:27:00-05:00               0  \n",
        "2014-05-04 15:28:00-05:00               0  \n",
        "2014-05-04 15:29:00-05:00               0  \n",
        "\n",
        "[210 rows x 8 columns]"
       ]
      }
     ],
     "prompt_number": 88
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x=np.arange(10)\n",
      "ys = [i+x+(i*x)**2 for i in range(10)]\n",
      "\n",
      "from matplotlib import cm\n",
      "colors = iter(cm.rainbow(np.linspace(0, 1, len(ys))))\n",
      "for y in ys:\n",
      "    plt.scatter(x, y, color=next(colors))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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kSSkDkiRJkiSlDEiSJEmSlDIgSZIkSVLKgCRJkiRJKQOSJEmSJKUMSJKkrheN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\nUBJnx2toAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f827eac6110>"
       ]
      }
     ],
     "prompt_number": 89
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.mean()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 90,
       "text": [
        "('air conditioner', 1)     3376.033333\n",
        "('appliance', 1)             12.080952\n",
        "('dish washer', 1)          233.214286\n",
        "('electric furnace', 1)     821.609524\n",
        "('fridge', 1)                97.666667\n",
        "('microwave', 1)             14.038095\n",
        "('sockets', 1)                0.000000\n",
        "('sockets', 2)               15.995238\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 90
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.set_palette(\"Set3\", n_colors=12)\n",
      "df.plot(kind='area')\n",
      "plt.xlabel(\"Time\")\n",
      "plt.ylabel(\"Power (W)\")\n",
      "plt.tight_layout()\n",
      "plt.savefig(\"submetered.png\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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WpRk/fiKbNr2Jy+VLX11dDfhawOvqapstk6IoZGQMpKyslL17dwNQX1+HqqrN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\n2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roJ3xAhRT2tfXBHpAq2tS95akl/bN0ETvg3q8MkQ2smSKd11eJZbl/+Jp7W+doshUYh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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f827efa9b90>"
       ]
      }
     ],
     "prompt_number": 91
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.timeseries(df)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "TypeError",
       "evalue": "'module' object is not callable",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
        "\u001b[1;32m<ipython-input-21-4a9cb826f9da>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msns\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtimeseries\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[1;31mTypeError\u001b[0m: 'module' object is not callable"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "we.store.window = TimeFrame(start='2014-05-04 12:00:00-05:00', end='2014-05-04 15:30:00-05:00')\n",
      "#elec.plot(kind='area');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 84
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Plot fraction of energy consumption of each appliance"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.palplot(sns.color_palette(\"Set3\", 12))\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAqsAAABGCAYAAADrXt2EAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f4d7357fc50>"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.choose_colorbrewer_palette()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "AttributeError",
       "evalue": "'module' object has no attribute 'choose_colorbrewer_palette'",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
        "\u001b[1;32m<ipython-input-25-4e5f328279d6>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msns\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mchoose_colorbrewer_palette\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[1;31mAttributeError\u001b[0m: 'module' object has no attribute 'choose_colorbrewer_palette'"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fraction = elec.submeters().fraction_per_meter().dropna()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "1/8 ElecMeter(instance=2, building=22, dataset='WikiEnergy', appliances=[Appliance(type='air conditioner', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "2/8 ElecMeter(instance=3, building=22, dataset='WikiEnergy', appliances=[Appliance(type='dish washer', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "3/8 ElecMeter(instance=4, building=22, dataset='WikiEnergy', appliances=[Appliance(type='electric furnace', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "4/8 ElecMeter(instance=5, building=22, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "5/8 ElecMeter(instance=6, building=22, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=2)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "6/8 ElecMeter(instance=7, building=22, dataset='WikiEnergy', appliances=[Appliance(type='microwave', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "7/8 ElecMeter(instance=8, building=22, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "8/8 ElecMeter(instance=9, building=22, dataset='WikiEnergy', appliances=[Appliance(type='appliance', instance=1)])"
       ]
      }
     ],
     "prompt_number": 93
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Create convenient labels\n",
      "labels = elec.get_appliance_labels(fraction.index)\n",
      "plt.figure(figsize=(8,8))\n",
      "fraction.plot(kind='pie', labels=labels);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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xTes6iIjiRVaZKExIc3ORuxgX1+EgJS+n1GS1aF0GEVHcSC8qMOdOGH+11nXQ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\nUBYCAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f827eee1710>"
       ]
      }
     ],
     "prompt_number": 94
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Select meters on the basic of appliance category"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "elec.select_using_appliances(category='heating')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "MeterGroup(meters=\n",
        "  ElecMeter(instance=7, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric furnace', instance=1)])\n",
        "  ElecMeter(instance=11, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric water heating appliance', instance=1)])\n",
        ")"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Find all appliances with a particular type of motor\n",
      "elec.select_using_appliances(category='single-phase induction motor')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 18,
       "text": [
        "MeterGroup(meters=\n",
        "  ElecMeter(instance=2, building=11, dataset='WikiEnergy', appliances=[Appliance(type='air conditioner', instance=1)])\n",
        "  ElecMeter(instance=5, building=11, dataset='WikiEnergy', appliances=[Appliance(type='dish washer', instance=1)])\n",
        "  ElecMeter(instance=6, building=11, dataset='WikiEnergy', appliances=[Appliance(type='spin dryer', instance=1)])\n",
        "  ElecMeter(instance=7, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric furnace', instance=1)])\n",
        "  ElecMeter(instance=10, building=11, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)])\n",
        ")"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Training and disaggregation"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Train\n",
      "co = CombinatorialOptimisation()\n",
      "co.train(elec)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Disaggregate\n",
      "disag_filename = join(data_dir, 'wikienergy-disag.h5')\n",
      "output = HDFDataStore(disag_filename, 'w')\n",
      "co.disaggregate(elec.mains(), output)\n",
      "output.close()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "vampire_power = 321.0 watts\n"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Alternatively, a model could be specified manually:\n",
      "\n",
      "```python\n",
      "co.model = [\n",
      "    {'states': [0,  100], 'training_metadata': ('television', 1)},\n",
      "    {'states': [0, 2000], 'training_metadata': ('electric furnace', 1)}\n",
      "    ]\n",
      "```"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Examine learned model"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for model in co.model:\n",
      "    print_dict(model)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<ul><li><strong>states</strong>: [   0  887 2970]</li><li><strong>training_metadata</strong>: ElecMeter(instance=2, building=11, dataset='WikiEnergy', appliances=[Appliance(type='air conditioner', instance=1)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f0d9eaf3950>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [ 0 13 77]</li><li><strong>training_metadata</strong>: ElecMeter(instance=3, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=1)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f0d9edb0b50>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [ 0 11 12]</li><li><strong>training_metadata</strong>: ElecMeter(instance=4, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=2)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f0d9e7e4110>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [   0  197 1030]</li><li><strong>training_metadata</strong>: ElecMeter(instance=5, building=11, dataset='WikiEnergy', appliances=[Appliance(type='dish washer', instance=1)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f0d9e7e42d0>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [0]</li><li><strong>training_metadata</strong>: ElecMeter(instance=6, building=11, dataset='WikiEnergy', appliances=[Appliance(type='spin dryer', instance=1)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f0d9e7e4590>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [  0  15 520]</li><li><strong>training_metadata</strong>: ElecMeter(instance=7, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric furnace', instance=1)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f0d9e7e4f50>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [  0  34 789]</li><li><strong>training_metadata</strong>: ElecMeter(instance=8, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=3)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f0d9e7e4b50>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [ 0 49 52]</li><li><strong>training_metadata</strong>: ElecMeter(instance=9, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=4)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f0d9e7e4b90>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [  0 138 463]</li><li><strong>training_metadata</strong>: ElecMeter(instance=10, building=11, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f0d9e7e4610>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [ 0 17 34]</li><li><strong>training_metadata</strong>: ElecMeter(instance=11, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric water heating appliance', instance=1)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f0d9e7e4810>"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Examine disaggregated data"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "disag = DataSet(disag_filename)\n",
      "disag_elec = disag.buildings[building_number].elec\n",
      "disag_elec.plot()\n",
      "disag.store.close()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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tnzRpEtu2bWPv3r0cOHCAOXPmcO211+Ls7MyRI0cc9TIyMmjXrh0AAQEBHDp0qML2jDHE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\nv2qQ7ANxKTvf8bHzlSv1Oc7TpiVfZ+hQvUa9Tx+9K7jTtVu5UndKAXd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lDVTtN7b7Cu/3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fMdUkP/n703D5OkKtPF33NORGRlVlVvdEN3Q7PZrYKCCwp6GxW5zKA413HGBXVcfuPci4p3hjs6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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f0d9cd2dad0>"
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Calculate accuracy of disaggregation"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "disag = DataSet(disag_filename)\n",
      "disag_elec = disag.buildings[building_number].elec\n",
      "\n",
      "f1 = f1_score(disag_elec, elec)\n",
      "f1.index = disag_elec.get_appliance_labels(f1.index)\n",
      "f1.plot(kind='bar')\n",
      "plt.xlabel('appliance');\n",
      "plt.ylabel('f-score');\n",
      "\n",
      "disag.store.close()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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WzB4h6Th3f9L8+HGS7uvuJy99zlmSXuzuHzKzP5T0Tnf/0x2cmxnY3fLt7c/X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\nbl/Dg70pVVXu1T1BSa6rqj1a5xgTP5MXhvd5MpL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       "text": [
        "<matplotlib.figure.Figure at 0x7f0d9c0fe690>"
       ]
      }
     ],
     "prompt_number": 23
    }
   ],
   "metadata": {}
  }
 ]
}